Current methods for guiding hot-tier insertion decisions rely on global rules for collection of access information and ultimately for determining what data should be inserted into a hot-tier.
However, the current methods suffer from drawbacks including an inability to efficiently cope with a large amount of accesses to be logged. Specifically, the global rules require that either the number of accesses logged be reduced to stop or limit the amount of memory used for logging or allow the logging process to consume an ever-growing amount of memory. In the first instance, the quality of the logging will decrease and thus data promoted to a higher tier will be less likely to result in a hit rate increase. In the second instance, the amount of memory used may grow so large as to cause a noticeable decrease in performance for the system.
Therefore, what is needed is an improved method for guiding hot-tier insertion decisions.